Currently tracking 498 active AI roles, down 12% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $98k–$1030k (avg $233k).
Google has 584 active AI-related job listings. The majority of these roles are focused on agents, representing 40% of the total, and serving infrastructure, at 26%. The most frequent technical tags include model_serving, agent_orchestration, and evals. Over the last 30 days, Google has added 413 new AI roles, a 105% increase compared to the preceding 30-day period.
Google currently has 586 active AI-related roles in our index. The most common open titles are: Software Engineer (5), AI Adoption Customer Engineer, Google Cloud (3), Conversational AI Consultant (2), Engineering Manager, Egregious Abuse Protection (2), Forward Deployed Engineer III, Generative AI, Google Cloud (2). Most positions are in Engineering and Product.
Google's active AI hiring is concentrated in: agents (43%), serving infrastructure (25%), application (19%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Google is hiring AI talent in: United States (376 roles), India (53 roles), Singapore (40 roles), Switzerland (20 roles).
Job postings at Google most frequently mention: Software Engineering, Algorithms & Data Structures, System Design, Computer Architecture, Machine Learning.
In the past 30 days, Google has posted 571 new AI-related roles. That is a +22% change versus the prior 30 days (469 → 571).
| Title | Stage | AI score |
|---|---|---|
| Senior Applied ML Engineer, Graph Neural Network, ML Frontiers Senior Applied ML Engineer focused on Graph Neural Networks within the Graph Flow platform, bridging pioneering models with enterprise solutions. The role involves defining new features, technical leadership, literature reviews, experimentation, efficient implementation on target hardware, and productionizing components. It also includes mentoring and collaborating with clients and research partners, with a focus on applied research and engineering. | ServePost-train | 8 |
| Software Engineer III, AI/ML, Sensor Fusion, XR Software Engineer III at Google working on AI/ML for Sensor Fusion in XR devices. The role involves developing foundational visual-inertial fusion for odometry, localization, and mapping, powering AndroidXR devices. Responsibilities include writing product/system development code, collaborating on design and code reviews, triaging issues, and implementing solutions in ML areas, utilizing ML infrastructure, and contributing to model optimization and data processing. |
| Serve |
| 7 |
| Engineer III, AI/ML, Online Calibration, XR Google is seeking an Engineer III, AI/ML for their Online Calibration team within the XR division. This role focuses on developing and implementing AI/ML solutions, utilizing ML infrastructure, and contributing to model optimization and data processing for next-generation XR devices. The engineer will write product/system code, collaborate with peers, triage issues, and implement solutions in specialized ML areas, potentially including speech/audio or reinforcement learning. | Serve | 7 |
| Software Engineer III, ML Pipeline Development, XR Software Engineer III, ML Pipeline Development, XR role focuses on productionizing advanced models and pipelines for on-device and server-based XR applications. Responsibilities include developing algorithms and frameworks for end-to-end pipeline development, optimizing system performance for hardware constraints, and ensuring critical power KPIs are met. Training ML models is not a requirement. | Serve | 7 |
| Software Engineer III, Spatial AI, XR Software Engineer III, Spatial AI, XR role focused on full-stack productionization and technical integration of on-device AI products for XR devices. Responsibilities include object tracking pipelines, API design, platform optimizations, and ensuring AI product quality and performance on target devices. | ServeAgent | 7 |
| Software Engineer III, AI/ML, DSP/HTP Optimisation Software Engineer III at Google, focusing on optimizing ML model performance on specialized hardware (DSP/HTP) to meet strict power and thermal constraints. This role involves hardware-specific optimizations, power profiling, and ensuring ML model efficiency within system architecture. | Serve | 7 |